code: def initialize(config_file_path: str):
      """
      Loads 'language-pair to NMT model mapping'
      """
      __MODELS_DICT = None
  
      logging.info("Starting NMT service")
      logging.info(
          f"I will attempt to load all the models listed in {config_file_path}."
      )
      logging.info(
          f"Edit {config_file_path} to disable models you don't need."
      )
      if torch.cuda.is_available():
          logging.info("CUDA is available. Running on GPU")
      else:
          logging.info("CUDA is not available. Defaulting to CPUs")
  
      # read config
      with open(config_file_path) as f:
          __MODELS_DICT = json.load(f)
  
      if __MODELS_DICT is not None:
          for key, value in __MODELS_DICT.items():
              logging.info(
                  f"Loading model for {key} from file: {value}"
              )
              if value.startswith("NGC/"):
                  model = nemo_nlp.models.machine_translation.MTEncDecModel.from_pretrained(
                      model_name=value[4:]
                  )
              else:
                  model = nemo_nlp.models.machine_translation.MTEncDecModel.restore_from(
                      restore_path=value
                  )
              if torch.cuda.is_available():
                  model = model.cuda()
              MODELS_DICT[key] = model
      else:
          raise ValueError(
              "Did not find the config.json or it was empty"
          )
      logging.info("NMT service started")
  
file_path: NeMo/tools/nmt_webapp/nmt_service.py
imports: import json
  import time
  import flask
  import torch
  from flask import Flask, json, request
  from flask_cors import CORS
  import nemo.collections.nlp
  from nemo.utils import logging
label_desc: Use image node_id 1 for calling a global function with example usage: initialize(config_file_path) without return types